Senior Software Developer – Data Analytics

Caseware is one of Canada's original Fintech companies, having led the global audit and accounting software industry for over 30 years, with more than 500,000 users across 130 countries and available in 16 different languages. While you might not have heard of us (yet) over 36,000 accounting and audit professionals list Caseware as a skill on their LinkedIn profiles! Overview of the Role Caseware is a global leader in cloud-enabled audit, assurance, and financial reporting solutions, helping accounting and assurance professionals work smarter with data they can trust. As a Senior Software Developer, you will be a hands-on technical leader who drives the design, development, and delivery of cloud-based solutions that are transforming how financial audits are performed worldwide. You will own complex technical problems end-to-end while coaching and leading a small squad of developers, helping them grow their skills and raise the engineering bar together. Working closely with Product and Design, you'll shape our roadmap from a technical perspective and drive iterative improvements across the entire software development lifecycle. You will be part of the Data Analytics department, committed to delivering state-of-the-art data lifecycle management and analytical solutions that enable our global distributor network to develop and customize products that meet their market needs. The squad you lead is responsible for developing a Cloud Data Analytics platform that runs thousands of concurrent import and analytic jobs in parallel across different workloads. 📍 Location: This is a fully remote position located in Colombia. Contact Maira Russo - Senior Talent Acquisition Partner What you'll be doing: Design and build key features and architectural improvements end-to-end — from technical discovery and system design through implementation, testing, and production support. Write production code daily in critical services, pipelines, and frameworks, using modern cloud-native patterns and technologies. Provide mentorship to the other developers on your team through design reviews, pair programming, and code reviews. Build deep expertise in the technology and architecture powering the Data Analytics Platform and use that knowledge to drive sound technical decisions. Collaborate with Product and Engineering to disambiguate requirements, surface technical uncertainty, and clearly communicate trade-offs and risks. Champion engineering excellence by keeping trunk/master green, stable, and deployable through strong CI/CD, testing, and operational practices. Coordinate with DevOps/CloudOps teams to ensure your squad has the tooling, infrastructure, and support needed to ship confidently. Own production reliability for the systems your squad manages, driving continuous improvement through post-mortems and root cause analysis. Provide 24/7 production support for the systems your team manages, driving continuous improvement in this area through post-mortems and root cause analysis. What you'll bring: 5+ years hands-on experience with Java 17+ (Spring Boot), microservice architecture, and developing enterprise SaaS applications on AWS. Extensive experience building and evolving cloud-native, data analytics platforms in production. Strong system design expertise, particularly in distributed systems, event-driven architectures, and large-scale data processing. Deep knowledge of analytics workflows, with an eye toward performance and correctness. An AI-native mindset — you instinctively reach for AI-powered tools and techniques as a first approach to problem-solving, planning, design, troubleshooting, code generation, debugging, and knowledge discovery. Proven ability to influence architectural direction, drive alignment across teams, and lead initiatives beyond your immediate scope. Comfort operating in ambiguity, with the ability to make sound technical decisions and clearly communicate risks and trade-offs. Agentic engineering and AI tools expectations As a member of this team, you are expected to integrate AI-assisted development into your daily workflow. This means using AI tools strategically to accelerate delivery, improve code quality, and solve problems faster, while maintaining strong engineering judgment and accountability for all work that ships. Proficiently use agentic code generation tools in your daily IDE workflow. Use conversational AI assistants for pair programming, design discussion, debugging, and documentation. Critically evaluate all AI-generated output before committing, verify correctness, security, and alignment with team standards. Identify routine or well-scoped tasks as candidates for agentic automation, and propose improvements to your tools/workflows to support this. Build feedback loops: document what worked, what failed, and why, to improve future agent performance and team understanding. Collaborate with your team to design and instrument AI-powered developer tooling; measure its impact on velocity an